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To 16-fold involving the trials using the highest and lowest total doses. The Immune Epitope Database (IEDB, utilizes the Ontology for Biomedical Investigations (OBI) and numerous further ontologies to represent immune epitope mapping experiments. Here, we describe our experiences using this representation to be able to give enhanced database search functionality. We applied a simple approach to incorporate the positive aspects with the data captured in a formal ontology directly into the user web interface, resulting in an improved user practical experience with minimal alterations for the database itself. The integration is easy to retain, supplies standardized terms and definitions, and allows for subsumption queries. In addition to these immediate added benefits, our long-term aim is to allow true semantic integration of data and knowledge within the biomedical domain. We describe our progress MI-538 cost towards that objective and what we perceive as the primary obstacles.The IEDB can be a totally free resource that catalogs published experimental data with regards to the recognition of epitopes by adaptive immune receptors. This can be accomplished by a group of curator scientists who study relevant manuscripts and extract the data following a set of established suggestions [1]. In order to represent the information within a systematic and interoperable manner, the IEDB actively contributes to several Open Biological and Biomedical Ontology (OBO) projects [2]. The closest of these collaborations has been with the Ontology for PubMed ID: Biomedical Investigations (OBI), an integrated ontology for the description of biological and clinical investigations [3]. OBI represents the experimental design, protocols, supplies, and instruments utilized in biomedical investigations, the information generated and the form of analyses performed. Previously, we utilized OBI to model and export the immunological experiments described inside the IEDB, enabling reasoning and driving database schema redesign [4,5]. Right here we describe a deeper integration of IEDB assay forms with OBI and discuss the quite a few positive aspects for usability and querying. We close using a general discussion of your fees and added benefits of integrating scientific data with ontologies, seeking beyond the scope of IEDB, and give our point of view on future prospects.?2013 Vita et al; licensee BioMed Central Ltd. This can be an Open Access post distributed below the terms in the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, supplied the original work is properly cited.Vita et al. Journal of Biomedical Semantics 2013, 4(Suppl 1):S6 two ofUsing ontologies to represent assays in the IEDB IEDB curators collect a wide selection of details concerning the experiments they curate. An accurate classification with the type of assays performed is important to get a correct understanding of an experiment and also the reported final results. Initially, IEDB curators surveyed relevant epitope publications and itemized the kinds of assays that had been encountered. Some assay sorts have been straightforward and very easily described, like tetramer staining, though other individuals have been extra complex, such as assays that assess the effect on disease development of immunizing mice with an epitope. A list of assay sorts was produced and employed as a controlled vocabulary by curators adding new experiments towards the database (Figure 1a). This list-based strategy was very limited and did not.

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